tailieunhanh - Báo cáo khoa học: "Generating Fine-Grained Reviews of Songs From Album Reviews"

Music Recommendation Systems often recommend individual songs, as opposed to entire albums. The challenge is to generate reviews for each song, since only full album reviews are available on-line. We developed a summarizer that combines information extraction and generation techniques to produce summaries of reviews of individual songs. We present an intrinsic evaluation of the extraction components, and of the informativeness of the summaries; and a user study of the impact of the song review summaries on users’ decision making processes. . | Generating Fine-Grained Reviews of Songs From Album Reviews Swati Tata and Barbara Di Eugenio Computer Science Department University of Illinois Chicago IL USA stata2 bdieugen @ Abstract Music Recommendation Systems often recommend individual songs as opposed to entire albums. The challenge is to generate reviews for each song since only full album reviews are available on-line. We developed a summarizer that combines information extraction and generation techniques to produce summaries of reviews of individual songs. We present an intrinsic evaluation of the extraction components and of the informativeness of the summaries and a user study of the impact of the song review summaries on users decision making processes. Users were able to make quicker and more informed decisions when presented with the summary as compared to the full album review. 1 Introduction In recent years the personal music collection of many individuals has significantly grown due to the availability of portable devices like MP3 players and of internet services. Music listeners are now looking for techniques to help them manage their music collections and explore songs they may not even know they have Clema 2006 . Currently most of those electronic devices follow a Universal Plug and Play UPNP protocol UPN 2008 and can be used in a simple network on which the songs listened to can be monitored. Our interest is in developing a Music Recommendation System Music RS for such a network. Commercial web-sites such as Amazon www. and Barnes and Nobles www. have deployed Product Recommendation Systems Product RS to help customers choose from large catalogues of products. Most Product RSs include reviews from customers who bought or tried the product. As the number of reviews available for each individual product increases RSs may overwhelm the user if they make all those reviews available. Additionally in some reviews only few sentences actually describe the recommended .